By Jason Macdonald
The carbon emissions mitigation and sequestration field is riddled with uncertainties, and biofuel emissions are no exception. While the debate over which carbon mitigation techniques are the most effective goes on in both the scientific and political spheres, the present analysis tries to pull together much of the established emissions literature for various biofuels and identify the discrepancies between them. The analysis attempts to determine the sources of these discrepancies and identify potential areas for future research to reduce this uncertainty. Greenhouse gas emissions are considered from a full fuel life cycle perspective.
The carbon emissions mitigation and sequestration field is riddled with uncertainties, and biofuel emissions are no exception. While the debate over which carbon mitigation techniques are the most effective goes on in both the scientific and political spheres, the present analysis tries to pull together much of the established emissions literature for various biofuels and identify the discrepancies between them. The analysis attempts to identify the sources of these discrepancies and potential areas for future research to reduce this uncertainty.
In order to get a complete understanding of the net greenhouse gas emissions from combusting biofuels, previous research investigating biofuels from a full fuel life cycle perspective was examined. A generalized inventory of the life cycle phases of biofuel system is shown in Figure 1. The dotted line represents the boundaries of the systems. Greenhouse gases (GHGs) are the only input or output of concern to us, as shown. GHG emissions arrows represent the aggregate of emissions measurable at the process underway and all upstream emissions associated with the manufacture of consumed products during each process.
The present discussion focuses on the most common biofuels in the United States, ethanol and biodiesel. In the case of ethanol, they are considering both 1st generation ethanol from the fermentation of corn starch and cellulosically derived 2nd generation fuels from switchgrass and corn stover. The biodiesel is from the transesterification of soybean oil with fossil methanol.
Biodiesel is a renewable, domestic substitute for petroleum diesel fuel. It can be used in any diesel engine without modification in any concentration. It is a product of a reaction between lipids (typically vegetable oil) and an alcohol, with a byproduct of glycol. There are many ways to accomplish this, but the most common is transesterification. The process steps for transesterification are reactant preparation, transesterification, separation, and purification (Coronado, de Carvalho Jr, & Silveira, 2009). There are many possible feedstocks, but the most common first generation feedstocks are soybean oil, rapeseed oil, canola oil, sunflower oil, and palm oil (Demirbas, 2009). Two other feedstocks that have potential for biodiesel production are waste vegetable oil (WVO) and microalgae. WVO is very attractive because it is cheaply available and is recycled, so it has a high proportion of its life cycle emissions allocated to the initial use of the oil. Microalgae, while it has not been demonstrated at a commercial scale, has a much better land use efficiency, and thus has a great potential to offset much of the current petroleum demand (Demirbas, 2009).
The studies analyzed vary in the way that emissions results were reported. In cases where conversion was necessary, the density of biodiesel was taken to be 0.88kg/L and a lower heating value of 33.3MJ/L was used (Oak Ridge National Laboratory, 2003).
Ethanol is an alcohol that can be used as a vehicle fuel when combined with as little as 15% gasoline. It requires small modifications to the most prevalent gasoline engines, and has been gaining increasing traction in vehicle design in the US for the last decade. Ethanol is created by the fermentation of simple sugars (glucose). In the US, the most prevalent feedstock used to make ethanol is corn starch. There are two common processes that are used to synthesize ethanol from corn starch, wet milling and dry milling. Wet milling is a process designed to separate different products from the corn, including starch, oil, and specialty feed ingredients. Dry milling is a process in which shelled corn is hammer-milled. It yields starch for fermentation into ethanol and a mixture called distillers dried grains with solubles, which is often used as a feed supplement because of its high nutritional content (Graboski, 2002). Cellulosic ethanol processing is more involved, as the cellulose in biomass must be broken down so that it can be fermented. In most applications, an enzyme, or enzyme cocktail is used to break down the cellulosic material. Cellulosic ethanol is considered to be the second generation of ethanol fuels because it is expected to have a much higher net energy yield, require less land area, and have little impact on food systems. In this analysis, ethanol is considered to have a lower heating value of 21.1 MJ/L (Oak Ridge National Laboratory, 2003).
Life-cycle GHG emissions for various biofuels were compared across five studies, acknowledging different feedstocks. Figure 2, below, shows emissions factors for biodiesel, ethanol, and cellulosic ethanol from five studies, ranging between 0.52 kg CO2 per L of ethanol to 6.8 kg CO2 per L of biodiesel (Delucchi, 2006; Farrell, 2006; Hill, Nelson, Tilman, Polasky, & Tiffany, 2006; Sheehan et al., 2000; Spatari, Zhang, & MacLean, 2005). In the studies analyzed, there are 3 datasets for corn starch derived ethanol, two for cellulosic ethanol from switchgrass, one for cellulosic ethanol from corn stover, and three sets of data for biodiesel from soybean oil. The results show an incredible amount of variation that is difficult to explain, but some of the factors that provide a significant portion of the changes are discussed in the next section.
Discussion of discrepancies
The discrepancies among biofuel emissions assessments are due to a number of factors. These include differences in process inclusion in the life cycle inventories, the uncertainty in the inventory data, the assumptions used in the analyses, the life cycle assessment’s boundaries (spatial, temporal, etc.), and the allocation methodology for dealing with co-products (Davis, Anderson-Teixeira, & DeLucia, 2009). In some studies, it was unclear if the greenhouse gases emissions mentioned were in carbon dioxide equivalents, or simply the carbon dioxide emissions. Table 1 displays the phases that were included in each of the life cycle inventories included in this analysis. As you can see, there is a wide variation in which phases were included in the life cycle assessment, which starts to account for the wide variation. When available, the percentages of impact on the overall reported GHG emissions were included in the table. Life cycle costs associated with cultivation are often on a per hectare basis, implying that the assumptions of yields for a given crop may have a large impact on the inventory data (Farrell, 2006). In life cycle assessment, data is very difficult to come by, so a lot of these studies use generalized data that may not be accurate for the specific situation it is being applied to. Also, some studies assume a time period in which processing technology is more mature than it is currently, reducing the energy demand during biomass conversion. Finally, allocation of emissions to co-products is not done uniformly throughout the studies (sometimes not considered at all) and can lead to a wide variation in the reported results. Table 1: Phase Inclusion in Life Cycle Inventories
Soil and land use change effects were often overlooked. Some studies have suggested that land cover change can force the payback periods for the carbon emitted during that process to be on the order of hundreds of years (Fargione, Hill, Tilman, Polasky, & Hawthorne, 2008). While this is alarming, it would be interesting to see a fair comparison to the damage associated with exploring for more fossil fuel reserves to meet future demand as well as any allocation of the biogenic carbon removed during the land use change to other co-products. Most of the studies examined ignored the effects of land cover change, as well as soil emissions due to nitrogen fertilizer use. Those that did include such parameters reported widely varying results that were specific to the locations being considered, primarily due to varying soil types and above ground carbon densities(Adler, Grosso, & Parton, 2007; Reijnders & Huijbregts, 2008). Carbon sequestration rates in the soil and roots during crop production is included in some studies, having a major impact on the overall GHG emissions from biofuel production (Adler et al., 2007; Kim & Dale, 2005; Spatari et al., 2005). One study suggests that low input, high diversity grassland biomass can store up to 4.4 tons of C per hectare, per year, while a monocrop, such as corn, will only sequester 0.14 tons (Tilman, 2006). This is roughly equivalent to 1600 L of diesel fuel emissions per hectare under cultivation per year offset by the carbon stored.
Feedstock can play a major role in the overall life cycle greenhouse gas emissions. Feedstocks effect the agricultural emissions, energy content of the biomass, and the conversion process emissions. One specific study looked at rapeseed versus soybean feedstocks for biodiesel and found that the aggregate greenhouse gas emissions were largely dependent on the agricultural practices used for each feedstock (Reijnders & Huijbregts, 2008).
Life cycle assessments of biofuels are in need of some standard methodologies and a standard set of assumptions in order to create some consistency in the literature (Davis et al., 2009). Values for annual crop yield, inventories for farming practices, and a standard set of life cycle phases should all be established. Further data collection for cellulosic ethanol production needs to be gathered, and a better understanding of GHG fluxes due to fertilization and soil sequestration need is needed. Lastly, a strict set of rules for allocation procedures should be established for uniformity. The suggestions above may not be comprehensive, but I believe that they will make a significant impact in reducing the variability of life cycle GHG emissions reporting for biofuels.
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